Porous Silicon-Based Aptasensors: Toward Cancer Protein Biomarker Detection

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Arshavsky-Graham, S.; Ward, S.J.; Massad-Ivanir, N.; Scheper, T.; Weiss, S.M. et al.: Porous Silicon-Based Aptasensors: Toward Cancer Protein Biomarker Detection. In: ACS Measurement Science Au 1 (2021), Nr. 2, S. 82-94. DOI: https://doi.org/10.1021/acsmeasuresciau.1c00019

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Zum Zitieren der Version im Repositorium verwenden Sie bitte diesen DOI: https://doi.org/10.15488/16697

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The anterior gradient homologue-2 (AGR2) protein is an attractive biomarker for various types of cancer. In pancreatic cancer, it is secreted to the pancreatic juice by premalignant lesions, which would be an ideal stage for diagnosis. Thus, designing assays for the sensitive detection of AGR2 would be highly valuable for the potential early diagnosis of pancreatic and other types of cancer. Herein, we present a biosensor for label-free AGR2 detection and investigate approaches for enhancing the aptasensor sensitivity by accelerating the target mass transfer rate and reducing the system noise. The biosensor is based on a nanostructured porous silicon thin film that is decorated with anti-AGR2 aptamers, where real-time monitoring of the reflectance changes enables the detection and quantification of AGR2, as well as the study of the diffusion and target-aptamer binding kinetics. The aptasensor is highly selective for AGR2 and can detect the protein in simulated pancreatic juice, where its concentration is outnumbered by orders of magnitude by numerous proteins. The aptasensor’s analytical performance is characterized with a linear detection range of 0.05-2 mg mL-1, an apparent dissociation constant of 21 ± 1 μM, and a limit of detection of 9.2 μg mL-1 (0.2 μM), which is attributed to mass transfer limitations. To improve the latter, we applied different strategies to increase the diffusion flux to and within the nanostructure, such as the application of isotachophoresis for the preconcentration of AGR2 on the aptasensor, mixing, or integration with microchannels. By combining these approaches with a new signal processing technique that employs Morlet wavelet filtering and phase analysis, we achieve a limit of detection of 15 nM without compromising the biosensor’s selectivity and specificity.
Lizenzbestimmungen: CC BY-NC-ND 4.0 Unported
Publikationstyp: Article
Publikationsstatus: publishedVersion
Erstveröffentlichung: 2021
Die Publikation erscheint in Sammlung(en):Naturwissenschaftliche Fakultät

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